US8175145B2 - Post-processing for reducing quantization noise of an encoder during decoding - Google Patents
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
- G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
- G10L19/26—Pre-filtering or post-filtering
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0316—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude
- G10L21/0364—Speech enhancement, e.g. noise reduction or echo cancellation by changing the amplitude for improving intelligibility
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- G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
Definitions
- the present invention relates to a signal processing, in particular of digital signals in the telecommunications field, these signals being able, for example, to be speech, music, video or other signals.
- bit rate necessary to transmit an audio and/or video signal with sufficient quality is an important parameter in telecommunications.
- audio encoders have been developed in particular to compress the quantity of information necessary to transmit a signal.
- Certain encoders make it possible to achieve particularly high ratios of compression of the information.
- Such encoders usually use advanced techniques for modeling and quantizing the information. Therefore, such encoders transmit only models or partial data of the signal.
- the decoded signal although it is not identical to the original signal (since a portion of the information has not been transmitted because of the quantization operation), nevertheless remains very similar to the original signal.
- the difference, from the mathematical point of view, between the decoded signal and the original signal is then called “quantization noise”. It is also possible to speak of “distortion” introduced by encoding decoding.
- the compression processes of signals are often designed so as to minimize the quantization noise and, in particular, to make this quantization noise as inaudible as possible when it involves processing an audio signal.
- the noise may remain audible, on occasions, which, in certain circumstances, degrades the intelligibility of the signal.
- a perceptual postfilter of the type used for example in the speech decoders of CELP (for “Coded Excited Linear Prediction”) type. This involves filtering which improves the subjective quality at the price of distortion. Specifically, an attenuation of the signal is applied in the zones in which the quantization noise is the most audible (particularly between the formants).
- Current perceptual postfilters provide good results for speech signals, but less good results for other types of signals (music signals, for example).
- Harmonics and formants are well known spectral characteristics of speech but to apply this type of process to a signal other than speech generates great distortions. For example, the spectral richness of a music signal cannot be processed with such a simple signal model.
- perceptual postfilters can generate distortions because they are based on a model which is not precise enough. Moreover, the perceptual postfilter is usually ineffective in periods of silence.
- Another processing family aims at conventional noise-reduction processes in order to distinguish the effective signal from the spurious noise.
- This type of process therefore makes it possible to reduce the noise associated with the environment of signal capture and it is often used for speech signals.
- the present invention enhances the situation.
- the method with respect to the invention comprises:
- noise-reduction process means in this instance an operation of the type described above which consists in extracting the effective signal from a signal to be processed, filtering the spurious signals, for example by defining a gain function operating in a filter applied to the decoded signal. In this instance, the quantization noise is filtered in this way.
- noise-reduction process type specific to each type of compression encoding carried out is provided.
- the very manner of estimating the characteristics of the noise-reduction filter depends on the type of encoding carried out.
- the quantization noise itself depends heavily on the type of encoding carried out. It will be seen that it is possible to establish a variation of the quantization noise as a function of a variation of the decoded signal, and that this quantization noise variation is specific to the type of encoding used.
- the a priori information on the type of compression encoding is obtained during an encoder declaration procedure.
- the invention is particularly suited to the situation in which the compression encoding type is an encoding according to the G.711 standard.
- a further subject matter of the present invention is a device for processing a signal that is initially compression encoded according to a predetermined encoding type, then decoded.
- the device comprises:
- the device advantageously comprises means for applying the method described above.
- FIG. 1 representing a device TBQ of the aforementioned type downstream of the decoding unit DEC.
- a further subject of the present invention is a computer program designed to be stored in the memory of a processing device of the aforementioned type, and comprising instructions for calculating the quantization noise, and parameters of a quantization noise reduction filter, when these instructions are executed by a processor of the processing device.
- An advantageous embodiment may consist in providing an instruction set for each type of encoding used and, in each instruction set, in defining a variation of the quantization noise as a function of the decoded signal. Therefore, on receipt of the a priori information, a set of appropriate instructions is selected. With this instruction set:
- the instructions on the variation of the quantization noise may be programmed offline, on the basis of observations (theoretical or experimental according to the exemplary embodiments that will be described below) made on the type of encoding used.
- the manner, itself, in which these instructions are executed will be described in detail below, with reference to FIGS. 2 and 5 which may then form flow charts of a computer program within the meaning of the invention.
- the invention proposes a post-processing that is carried out after decoding and that uses a priori information on the characteristics of the quantization operation that the encoder carries out.
- the type of process (or “process model” according to the above generic terms) which will be chosen to process the signal is independent of the characteristics of the signal itself. Naturally, the process per se (particularly the estimation of the gain function) may depend on the signal, for example on its energy or its power. On the other hand, whether it involves processing a music signal, a speech signal or any other signal (of a harmonic, pulse, etc. nature), the type of process is the same and is based, for example, only on the energy of a received decoded frame.
- the invention makes it possible to reduce the quantization noise (and hence the distortion) that a compression encoder of the signal usually introduces applying a quantization operation.
- the present invention proposes, it is possible to keep the same encoding/decoding structure without making any modification thereto and yet to ensure a better quality of the decoded signal, and to do so without increasing the quantity of information to be transmitted by the encoder.
- the invention makes it possible to advantageously reduce the quantization noise alone, even in a period of silence, and to do so for any type of signal.
- the application of the invention does not cause a conventional noise reduction and therefore does not modify the noise associated with the environment of the capture of the signal.
- the application of the invention makes it possible to reduce, or even eliminate, the quantization noise, without distorting the signal and to do so for any type of signal, simply by using a priori information on the type of encoder used (for example the characteristics of the compression model of the encoder, the characteristics of the quantizer, or other characteristics).
- the present invention finds an advantageous application in the field of processing speech and music, and more generally in the processing of the signal, particularly of images, when any encoder introduces a quantization noise.
- the invention applies to all the fields in which there is the need to reduce a quantization noise of a signal.
- FIG. 1 illustrates schematically the general structure of a processing unit within the meaning of the invention
- FIG. 2 illustrates schematically the steps of a method within the meaning of the invention
- FIG. 3 illustrates a variation of the amplitude-compression law (called the “A law”), in an encoding according to the G.711 standard in order to illustrate an exemplary embodiment of the invention
- FIG. 4 illustrates the variation in the signal-to-quantization noise ratio RSB as a function of the load factor, this variation being drawn from the variation illustrated in FIG. 3 ,
- FIG. 5 illustrates the steps of an exemplary process in the case of encoding according to the G.711 standard, based in particular on the observations of the variations of FIGS. 3 and 4 ,
- FIG. 6 illustrates an example of the signal spectrum (the dashed curve) and of the quantization noise spectrum (the continuous curve) for encoding according to the G.722 standard
- FIG. 7 illustrates a waveform example of a speech signal S* (the top curve) and the corresponding signal-to-quantization noise ratio RSB (the bottom curve), for encoding/decoding according to the G.722 standard,
- FIG. 8 is a cloud of dots illustrating, for each segment of 80 samples, the correlation between the signal-to-noise ratio RSB and the energy of the signal, in an application to encoding/decoding according to the G.722 standard,
- FIG. 9 shows the signal segments (in black) in which the estimation error of the signal-to-quantization noise ratio RSB is greater than 6 dB while the ratio RSB is less than 25 dB, in the application to encoding/decoding according to the G.722 standard,
- FIG. 10 repeats the cloud of dots representing, for each segment, the energy of the noise as a function of the energy of the signal, illustrating in this instance the estimate of the noise level (dotted and dashed line), the zone in which the error of the estimate is less than 6 dB (dashed lines), and the delimitation for which the ratio RSB is greater than 25 dB (the solid line).
- the signal thus decoded, marked S* then has a quantization noise which is defined mathematically as a difference (S* ⁇ S) relative to the original signal S.
- a quantization noise reduction process unit TBQ is provided downstream of the decoder DEC in order to eliminate or at least limit the quantization noise in the signal S*.
- the unit TBQ comprises at least one input E in order to receive from the decoder DEC information INF on the type of encoding/decoding used, which makes it possible then to choose a noise-reduction processing model to be applied.
- the influence of the quantization noise in the received signal S* is estimated.
- a calculation model is provided for giving an estimate of the quantization noise BQ on the basis of the chosen model and as a function of the received signal S*.
- This calculation module can typically take the form of a combination of a processor and a working memory (not shown).
- the estimated noise BQ is simply processed by applying a conventional filter FIL to the signal S* in order finally to deliver a processed signal S* T .
- the parameters PAR of the filter FIL applied to the signal S* for example a gain function for the filtering of the signal
- the parameters PAR of the filter FIL applied to the signal S* are determined in order to reduce in particular the estimated quantization noise BQ.
- a noise-reduction processing model is determined (step S 3 ). It will be seen in the exemplary embodiments described below that the quantization noise reduction model chosen may be different, for example depending on whether the signal has been encoded/decoded according to the G.711 standard or encoded/decoded according to the G.722 standard.
- a quantization noise level specific to the chosen model is estimated (step S 4 ).
- RSB the level of quantization noise based on the calculation of the signal-to-quantization noise ratio (marked RSB).
- This information RSB depends on the decoded signal S*, but also on the type of encoding used. Therefore, the a priori knowledge of the encoding, by obtaining the information INF makes it possible, in combination with certain statistical characteristics of the signal S*, to estimate in this instance the signal-to-quantization noise ratio RSB.
- This step S 4 therefore requires an a priori knowledge of the type of encoder that has been used, information which can be obtained for example during a procedure for declaring the encoder called “the encoder transaction”, that is assumed to be acquired.
- the type of encoder, the characteristics of its compression model and of its quantizer Q make it possible to estimate a change in the signal-to-quantization noise ratio, as a function of certain statistical parameters of the signal, such as for example its variance, its power spectral density, or other parameters.
- This relationship between the signal-to-quantization noise ratio and the statistical parameters of the signal brings into play the laws specific to the encoder that will be described below, for a few exemplary embodiments.
- the necessary statistical parameters may be calculated by conventional estimators of magnitude (for example the variance). As a function of these estimates, an estimation of the signal-to-quantization noise ratio may be extrapolated.
- the estimates may be made without distinction in the time or frequency fields or any other time-frequency field (converted into wavelets for example).
- the next step S 5 consists in calculating the parameters of the filter for the reduction of the quantization noise in the received signal S*. Knowing the signal-to-noise ratio makes it possible to deduce therefrom the expression of a quantization noise reduction filter, this filter hereinafter being called the “postfilter” (downstream of the decoder). Specifically it is possible to deduce the expression of a digital filter the purpose of which is to reduce a noise most of whose characteristics are known a priori (its power spectral density for example) and the level of which is determined based on the estimate of the signal-to-quantization noise ratio obtained in the previous step S 4 .
- a priori its power spectral density for example
- the filter can be calculated in the frequency field and any short-term spectral attenuation technique may be applied (a spectral subtraction, a Wiener filter, or other technique).
- the calculation of the postfilter in step S 5 may be carried out in the time or frequency fields or any other time-frequency field.
- the noise-reduction processing step S 6 itself, means in this instance filtering the decoded signal S* via the postfilter calculated in step S 5 .
- This step S 6 may be carried out in the time or frequency field, depending upon the constraints associated with the application and the field of estimation of the parameters PAR and of the ratio RSB in the previous steps. This finally gives a frame TRi′ processed by reduction of the quantization noise in step S 7 .
- Described below is an exemplary embodiment of the invention for encoding/decoding according to the G.711 standard (according to the European law called the “A law”).
- the conventional digital representation of one-dimensional signals uses a uniform quantization of the samples. Therefore, if the capacity of the quantizer is not exceeded, the signal-to-quantization noise ratio (RSB) depends on the variance ⁇ x 2 of the signal, on the saturation levels x max determined by the dynamic range and naturally on the number of bits b used to represent the samples, according to an expression of the following type:
- the expression (1) is highly dependent on the value of this parameter ⁇ . It is noted in particular that the maximum signal-to-noise ratio is obtained for a full-scale signal and that it decreases rapidly if the amplitude of the signal diminishes.
- F ⁇ ( x ) ⁇ A ⁇ ⁇ x ⁇ / x max 1 + ln ⁇ ⁇ A ⁇ sgn ⁇ ⁇ x , 0 ⁇ ⁇ x ⁇ / x max ⁇ A - 1 x max ⁇ 1 + ln ⁇ ( A ⁇ ⁇ x ⁇ / x max ) 1 + ln ⁇ ⁇ A ⁇ sgn ⁇ ⁇ x , A - 1 ⁇ ⁇ x ⁇ / x max ⁇ 1 ( 2 )
- /x max ⁇ A ⁇ 1 ) is linear, engenders a uniform quantization law and is called hereinafter “uniform variation”, while the second variation of the compression law (A ⁇ 1 ⁇
- the average power Pm of a current block TRi (step S 52 ) is estimated and, from there, the load factor ⁇ , varying as the inverse of the square root of the average power (step S 53 ). It is considered specifically that the numerator x max of the load factor is constant in this instance (at a constant saturation level).
- the value found for the load factor ⁇ is compared with that of a threshold ⁇ s defining the point of inflection of the compression law ( FIG. 4 ), as follows:
- a Wiener filter may be provided as a gain function g(RSB).
- the expression of the Wiener filter f w may be given by the value of the signal-to-quantization noise ratio RSB calculated previously, taking account naturally of its frequency dependence with:
- ITU-T G.722 encoding standardized in 1988 for audioconference applications on 64 kbit/s digital channels, is still very widely used. It is a three-bit hierarchical encoding/decoding: 64, 56 and 48 kbit/s.
- the signal is divided into two subbands by a filter called QMF (for “Quadrature Mirror Filter”).
- QMF for “Quadrature Mirror Filter”.
- ADPCM for “Adaptive Differential Pulse Code Modulation” encoder.
- the high band is encoded on 2 bits per sample.
- the difference between the three bit rates comes from the low band which is encoded on 6 bits per sample for the highest bit rate, but it is possible to reserve the last or the last two bits for data transmission.
- the quality of the highest bit rate is very good, however the encoding noise becomes very audible and annoying for the lowest bit rate of 48 kbit/s.
- the quantization noise reduction process within the meaning of the invention can be advantageously applied in this case.
- the quantization noise spectrum (the solid-line curve) is always flat, irrespective of the signal spectrum (curve in dashed lines).
- the signal-to-quantization noise ratio depends on the average power of the signal and its nature.
- FIG. 7 it can be seen that the signal-to-quantization noise ratio (RSB) is well correlated with the average power of the signal S*.
- the ratio RSB has been estimated on segments of 80 samples (5 ms for a sampling frequency of 16 kHz).
- the representation in the form of clouds of dots in FIG. 8 even better illustrates the correlation between the average power of the signal (the axis of the abscissas) and the signal-to-quantization noise ratio (the axis of the ordinates), calculated by segments of 80 samples.
- FIG. 9 represents in black on a grey background the zones of the signal in which the ratio RSB estimation error is greater than 6 dB and the ratio RSB itself is less than 25 dB, that is to say the zones of the signal in which the estimator under-estimates the quantization noise, which causes the quantization noise reduction process to be less effective. It is possible however to note that these zones correspond to unvoiced signal segments, for which the quantization noise is less of a drawback because of the intrinsically noisy nature of the signal.
- FIG. 10 shows a diagram of noise power relative to the signal power, according to the empirical equation (5).
- the dot-and-dash line represents the estimate of the noise power.
- the dashed lines delimit the zone in which the estimation error is lower than 6 dB. Below the solid line, the ratio RSB is greater than 25 dB.
- the black dots correspond to the black segments of FIG. 9 .
- the estimate of the ratio RSB may be further refined by taking account, for example, of the prediction gain of the ARMA (autoregressive) filters which are used in the G.722 decoder.
- an advantageous application of the invention may, for example, aim to reduce the quantization noise of an ITU-G.711 standard encoder using the properties of the quantization law applied, in particular according to the A law in Europe.
- the quantization noise is white and it is possible to estimate the signal-to-quantization noise ratio and, from that, a gain function which makes it possible to reduce this noise.
- An object of an advantageous application of the invention is then the reduction of quantization noise in the process to extend the G.711 encoder to a widen band (ITU-T SG16, G.711WB).
- the invention applies to any type of encoding/decoding given that its intrinsic characteristics are known.
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Abstract
Description
-
- a “long term” section reinforces the harmonics (harmonics of the fundamental frequency) and hollows out the spectral valleys between these harmonics, and
- a “short term” section reinforces the formants and also hollows out the spectral valleys between these formants.
-
- an estimate of a quantization noise introduced by the compression encoding based on the decoded signal and information obtained a priori on the type of compression encoding,
- an estimate of a signal to quantization noise rate. and
- a determination, based on the estimated signal to quantization noise rate, of a filtering function to be applied to the decoded signal in order to apply an estimated quantization noise reduction process.
-
- a quantization noise reduction model is chosen based on information on the type of compression encoding, and
- a quantization noise reduction process is applied to the decoded signal according to the chosen model.
-
- on the basis of this model, the quantization noise that the compression encoding has introduced is estimated, and
- based on the estimated quantization noise, a filtering function (and in particular the parameters of this filtering function) is determined to be applied to the decoded signal in order to apply the quantization noise reduction process.
-
- based on the information of the type of encoding, a variation of the quantization noise is estimated as a function of at least one parameter of the decoded signal, and
- according to a current value of this parameter in the decoded signal, the quantization noise is estimated in order to determine the filtering function to be applied to the decoded signal having this current parameter value.
-
- a variation model of a signal-to-quantization noise ratio, as a function of at least one parameter of the decoded signal, and/or
- a spectral coloration of the quantization noise (that is to say a spectral variation of the quantization noise as a function of the characteristics of the decoded signal).
-
- means for estimating a quantization noise introduced by the compression encoding, based on the decoded signal and information obtained a priori on the type of compression encoding,
- means for estimating a signal to quantization noise ratio. and
- means for determining, based on the estimated signal to quantization noise ratio, a filtering function to be applied to the decoded signal in order to apply an estimated quantization noise reduction process.
-
- the quantization noise present in the decoded signal is calculated,
- and the parameters of the postfilter are calculated in correspondence with this quantization noise in order to limit, or even eliminate, this noise.
-
- compression encoded by an encoder COD of known type and applying in particular a quantization operation Q to the signal S,
- transmitted via a transmission channel CA, then
- decoded by a decoder DEC that is the counterpart of the encoder COD.
represents a parameter called the “load factor” which determines the quality of use by the signal of the quantizer's dynamic range, in which:
-
- xmax is the maximum possible digital amplitude level of a sample according to the chosen quantizer, and
- σx is the standard deviation of the signal (the square root of the variance) which, for a complete block of samples (or “frame”), can be estimated via the square root of the average power Pm of the signal on this block.
RSB unif=(20 log 2)b+10
RSB unif≈6.02b+4.77+10 log [A/(1+ln A)]−20 log(Γ)[dB]
RSB unif≈64.97−20 log(Γ)[dB] for b=8 (3)
RSB log=(20 log 2)b+10
RSB log≈6.02b −10[dB]
RSB log≈38.16 dB for b=8 (4)
-
- a first increasing portion, corresponding to the uniform variation of the compression law, and
- a next portion, that is constant, corresponding to the logarithmic variation of this law.
-
- the signal-to-quantization noise ratio that is given by the equations (3) and (4) above, and
- the well-known information according to which this noise is “white” for this type of encoding.
-
- if the load factor Γ is such that −20·log(Γ)>−20·log(Γs)=38.16−64.97˜=−27 dB (arrow ∘ at the output of the test T54), then the signal-to-quantization noise ratio is constant and is RSBM˜=+38 dB (the plateau in
FIG. 4 ), as fixed in the step S55, - otherwise (arrow n at the output of the test T54), then the signal-to-quantization noise ratio RSB can be calculated according to a linear variation as a function of the load factor drawn from the equation (3):
RSB=f(Γ)=65−20 log(Γ) [dB], as fixed in the step S56.
- if the load factor Γ is such that −20·log(Γ)>−20·log(Γs)=38.16−64.97˜=−27 dB (arrow ∘ at the output of the test T54), then the signal-to-quantization noise ratio is constant and is RSBM˜=+38 dB (the plateau in
-
- a thresholding of the postfilter, and/or
- a voice activity detector for speech signals (with a lighter processing of quantization noise reduction during the periods of speech inactivity).
RSB=P moy −CST [dB] (5)
where CST is a constant which, in the example of
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Cited By (4)
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US20100272181A1 (en) * | 2009-04-24 | 2010-10-28 | Toshiharu Tsuchiya | Image processing method and image information coding apparatus using the same |
US20110046947A1 (en) * | 2008-03-05 | 2011-02-24 | Voiceage Corporation | System and Method for Enhancing a Decoded Tonal Sound Signal |
US20110257984A1 (en) * | 2010-04-14 | 2011-10-20 | Huawei Technologies Co., Ltd. | System and Method for Audio Coding and Decoding |
US9431022B2 (en) | 2012-02-15 | 2016-08-30 | Renesas Electronics Corporation | Semiconductor device and voice communication device |
Families Citing this family (6)
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DK3537437T3 (en) * | 2013-03-04 | 2021-05-31 | Voiceage Evs Llc | DEVICE AND METHOD FOR REDUCING QUANTIZATION NOISE IN A TIME DOMAIN DECODER |
FR3007184A1 (en) * | 2013-06-14 | 2014-12-19 | France Telecom | MONITORING THE QUENTIFICATION NOISE ATTENUATION TREATMENT INTRODUCED BY COMPRESSIVE CODING |
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6058362A (en) * | 1998-05-27 | 2000-05-02 | Microsoft Corporation | System and method for masking quantization noise of audio signals |
US6128346A (en) * | 1998-04-14 | 2000-10-03 | Motorola, Inc. | Method and apparatus for quantizing a signal in a digital system |
US20030182104A1 (en) | 2002-03-22 | 2003-09-25 | Sound Id | Audio decoder with dynamic adjustment |
US6738428B1 (en) * | 1999-03-18 | 2004-05-18 | Oki Electric Industry Co., Ltd. | Apparatus and methods for decoding a predictively encoded signal and removing granular noise |
WO2005041170A1 (en) | 2003-10-24 | 2005-05-06 | Nokia Corpration | Noise-dependent postfiltering |
US20050117656A1 (en) * | 2002-01-25 | 2005-06-02 | Koninklijke Philips Electronics N.V. | Method and unit for substracting quantization noise from a pcm signal |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH0752844B2 (en) * | 1985-11-27 | 1995-06-05 | 日本電気株式会社 | Noise elimination circuit |
JPH03116197A (en) * | 1989-09-29 | 1991-05-17 | Matsushita Electric Ind Co Ltd | Voice decoding device |
JP3024468B2 (en) * | 1993-12-10 | 2000-03-21 | 日本電気株式会社 | Voice decoding device |
JP4358221B2 (en) * | 1997-12-08 | 2009-11-04 | 三菱電機株式会社 | Sound signal processing method and sound signal processing apparatus |
KR100477699B1 (en) * | 2003-01-15 | 2005-03-18 | 삼성전자주식회사 | Quantization noise shaping method and apparatus |
US20070223660A1 (en) * | 2004-04-09 | 2007-09-27 | Hiroaki Dei | Audio Communication Method And Device |
US8315863B2 (en) * | 2005-06-17 | 2012-11-20 | Panasonic Corporation | Post filter, decoder, and post filtering method |
-
2008
- 2008-06-13 EP EP08805992A patent/EP2153438B1/en active Active
- 2008-06-13 ES ES08805992T patent/ES2376178T3/en active Active
- 2008-06-13 AT AT08805992T patent/ATE531038T1/en not_active IP Right Cessation
- 2008-06-13 JP JP2010511708A patent/JP2010529511A/en active Pending
- 2008-06-13 WO PCT/FR2008/051057 patent/WO2009004225A1/en active Application Filing
- 2008-06-13 US US12/663,546 patent/US8175145B2/en active Active
-
2014
- 2014-09-04 JP JP2014180564A patent/JP5881791B2/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6128346A (en) * | 1998-04-14 | 2000-10-03 | Motorola, Inc. | Method and apparatus for quantizing a signal in a digital system |
US6058362A (en) * | 1998-05-27 | 2000-05-02 | Microsoft Corporation | System and method for masking quantization noise of audio signals |
US6738428B1 (en) * | 1999-03-18 | 2004-05-18 | Oki Electric Industry Co., Ltd. | Apparatus and methods for decoding a predictively encoded signal and removing granular noise |
US20050117656A1 (en) * | 2002-01-25 | 2005-06-02 | Koninklijke Philips Electronics N.V. | Method and unit for substracting quantization noise from a pcm signal |
US20030182104A1 (en) | 2002-03-22 | 2003-09-25 | Sound Id | Audio decoder with dynamic adjustment |
WO2005041170A1 (en) | 2003-10-24 | 2005-05-06 | Nokia Corpration | Noise-dependent postfiltering |
US20060116874A1 (en) * | 2003-10-24 | 2006-06-01 | Jonas Samuelsson | Noise-dependent postfiltering |
Non-Patent Citations (1)
Title |
---|
Chen et al., "Adaptive Postfiltering for Quality Enhancement of Coded Speech," IEEE Transactions on Speech and Audio Processing, vol. 3 (1), pp. 59-71 (Jan. 1995). |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110046947A1 (en) * | 2008-03-05 | 2011-02-24 | Voiceage Corporation | System and Method for Enhancing a Decoded Tonal Sound Signal |
US8401845B2 (en) * | 2008-03-05 | 2013-03-19 | Voiceage Corporation | System and method for enhancing a decoded tonal sound signal |
US20100272181A1 (en) * | 2009-04-24 | 2010-10-28 | Toshiharu Tsuchiya | Image processing method and image information coding apparatus using the same |
US8565312B2 (en) * | 2009-04-24 | 2013-10-22 | Sony Corporation | Image processing method and image information coding apparatus using the same |
US20110257984A1 (en) * | 2010-04-14 | 2011-10-20 | Huawei Technologies Co., Ltd. | System and Method for Audio Coding and Decoding |
US8886523B2 (en) * | 2010-04-14 | 2014-11-11 | Huawei Technologies Co., Ltd. | Audio decoding based on audio class with control code for post-processing modes |
US9646616B2 (en) | 2010-04-14 | 2017-05-09 | Huawei Technologies Co., Ltd. | System and method for audio coding and decoding |
US9431022B2 (en) | 2012-02-15 | 2016-08-30 | Renesas Electronics Corporation | Semiconductor device and voice communication device |
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WO2009004225A1 (en) | 2009-01-08 |
US20100183067A1 (en) | 2010-07-22 |
JP2010529511A (en) | 2010-08-26 |
ES2376178T3 (en) | 2012-03-09 |
EP2153438B1 (en) | 2011-10-26 |
ATE531038T1 (en) | 2011-11-15 |
JP5881791B2 (en) | 2016-03-09 |
EP2153438A1 (en) | 2010-02-17 |
JP2015007805A (en) | 2015-01-15 |
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